similar to: simple ts.plot question

Hi, I'm new to R, and I have searched helpfiles and this forum on my 2 questions. Hope you guys can help me out! :-) Many thanks in advance! Cheers, Lars Q1: I imported a csv file with columnames subject and class. There are about 1000 different classes... It looks like this: subject1, class1 subject1, class2 subject2, class1 subject2, class3 ... subject999, class1 subject999, class2

I have a multiple text files, separated by a single space, that I need to combine into a single data.frame. Below is the track I'm on using list.files to capture the names of the files and then lapply with read.table. But I run into problems making a usable dataframe out of the data. #Creating example data in similar format to data I have sub <- rep(1,10) trial <- seq(1,10,1) size

Hello everybody, I need an help because I don´t know if the command for the ANOVA analysis I am performing in R is correct. Indeed using the function aov I get the following error:"In aov (......) Error() model is singular" The structure of my table is the following: subject, stimulus, condition, sex, response Example: subject stimulus condition sex response

Hi I would like to transform a data frame like Subject Item Score Subject 1 Item 1 1 Subject 1 Item 2 0 Subject 1 Item 3 1 Subject 2 Item 1 1 Subject 2 Item 2 1 Subject 2 Item 3 0 .... *to * Subject Item1 Item2 Item3 .....Item N Subject1 1 0 1 Subject2 1 1 0 ........ SubjectP.. Apologize for the simple nature of my query but I am stuck.

I get the following message when using the reshape2 package line > tDat.m<- melt(Dataset) Using Item, Subject as id variables > tDatCast<- acast(tDat.m,Subject~Item) Aggregation function missing: defaulting to length Note Problem Statement- convert dataframe Subject Item Score 1 Subject 1 Item 1 1 2 Subject 1 Item 2 0 3 Subject 1 Item 3 1 4 Subject 2 Item 1 1 5

I am looking for help to analyze an unbalanced AB/BA cross-over design by requesting the type III SS ! # Example 3.1 from S. Senn (1993). Cross-over Trials in Clinical Research outcome<-c(310,310,370,410,250,380,330,270,260,300,390,210,350,365,370,310,380,290,260,90,385,400,410,320,340,220) subject<-as.factor(c(1,4,6,7,10,11,14,1,4,6,7,10,11,14,2,3,5,9,12,13,2,3,5,9,12,13))

I am trying to specify a mixed model for my research, but I can't quite get it to work. I've spent several weeks looking thru various online sources to no avail. I can't find an example of someone trying to do precisely what I'm trying to do. I'm hoping some smart member of this mailing list may be able to help. First off, full disclosure: (1) I'm an engineer by trade, so

Hi all, I have a matrix of 474 rows (samples) with 565 columns (variables). each of the 474 samples belong to one of 120 groups, with the groupings as a column in the above matrix. For example, the group column would be: 1 1 1 2 2 2 . . . 120 120 I want to randomly select one from each group. Not all the groups have the same number of samples, some have 4, some 3 etc. Is there a function to

R users, I intention is to calculate some summary statistics across factor levels. I know that in Hmisc package there is a summary function which produces neat summary statistics when using "cross" option. I would like to produce similar output with N and Missing columns but produce a data.frame. Is there any built-in function for that? #example data install.packages("Hmisc")

Full_Name: Kevin Wright Version: 1.4 OS: Windows 95 Submission from: (NULL) (170.54.59.160) Note: This was the 1.4 build for Windows that Brian Ripley made available. The first example in the help for reshape doesn't work for me. When I cut and paste, this is what happens: > data(Indometh,package="nls") > summary(Indometh) Subject time conc

Hi, I was trying to run the example of Indomethacin kinetics from the book: ## From Pinheiro/Bates, Mixed-Effects-Models in S and S-Plus, ## Springer, Second Printing 2001, Section 6.2 library(nlme) plot(Indometh) fm1Indom.nls <- nls(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) summary(fm1Indom.nls) plot(fm1Indom.nls,Subject~resid(.),abline=0) ## .... the last plot command gives me the

Given a data frame of a categorical variable and two continuous variables, I would like to display one continuous variable against the other for each value of the categorical variable, all superimposed on the same plot. For example: data(Indometh); str(Indometh) Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 66 obs. of 3

Hi there, I'm quite new to R (and statistics), and I like it (both)! But I'm a bit lost in all these packages, so could someone please give me a hint whether there exists a package for fitting exponential curves (of the type t --> \sum_i a_i \exp( - b_i t)) on a noisy signal? In fact monoexponential decay + polynomial growth is what I'd like to try. Thanks in advance,

Hi All, I am currently preparing some form of slideshow introducing R and its capabilities for some colleagues. The thing will be about 30 mins, and I'd like to have some "pretty pictures" and some "amazing facts" (I'm trying to sell, obviously :)). Can I ask if it's possible to easily retrieve a gross figure of the number of functions in R considering the

Hi, It's probably a simple issue but I'm struggling with that. I'll use the example shown in the help page. head(Indometh) wide <- reshape(Indometh, v.names="conc", idvar="Subject", timevar="time", direction="wide") head(wide) reshape(wide, idvar="Subject", varying=list(2:12), v.names="conc",

I postulate the following model AC <- glmer(Accuracy ~ RT*Group + (1+RT|Group:subject) + (1+RT|Group:Trial), data = da, family = binomial, verbose = T) Here I predict Accuracy from RT, Group (which has values 0 or 1) and the interaction of Group and RT (those are the fixed effects). I also estimate the random effects for both intercepts and slopes for subjects and different trials.

Hello R list, This is a question for anyone who has used the by() command. I would like to perform a regression on a data frame by several factors. Using by() I think that I have able to perform this using the following: > lm.r <- by(master, list(Sectionf=Sectionf, startd=startd), function(x) lm (tot.c ~ starttime, data = x)) So that is, I would like to perform separate regressions for

Hello, I'm producing text from my data.frame using cat function. I would like to use for loop to export each column in my data.frame into separate text files. Here is the example code r <- t(Indometh) for (i in 1:ncol(r)) { cat("Some text,", "\n") cat("\n") cat("More text, More text, More text") cat("\n")

Dear R community, I am trying to fit an nlme model where I want to estimate the fixed effects of two treatments on the parameters on the following equation Photo~(a*(1-exp(-c*PARi/a)))-b I was able to fit a simple model without covariates following the method described in Mixed-Effects Methods and Classes for S and S-PLUS, version 3.0, but when I add the covariates, I get the error "

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':